code: def test_correctness(self):
      sequence = (
          np.arange(480).reshape((2, 3, 4, 4, 5)).astype("float32")
          / 100
      )
      expected_output = np.array(
          [
              [
                  [[0.48694518, 0.48694518], [0.50237733, 0.50237733]],
                  [[0.5461202, 0.5461202], [0.5598283, 0.5598283]],
              ],
              [
                  [[0.8661607, 0.8661607], [0.86909103, 0.86909103]],
                  [[0.8774414, 0.8774414], [0.8800861, 0.8800861]],
              ],
          ]
      )
      if backend.config.image_data_format() == "channels_first":
          sequence = sequence.transpose((0, 1, 4, 2, 3))
          expected_output = expected_output.transpose((0, 3, 1, 2))
      layer = layers.ConvLSTM2D(
          filters=2,
          kernel_size=3,
          kernel_initializer=initializers.Constant(0.01),
          recurrent_initializer=initializers.Constant(0.02),
          bias_initializer=initializers.Constant(0.03),
      )
      output = layer(sequence)
      self.assertAllClose(
          expected_output,
          output,
      )
  
file_path: keras/keras/layers/rnn/conv_lstm2d_test.py
imports: import numpy
  import pytest
  from keras import backend
  from keras import initializers
  from keras import layers
  from keras import testing
label_desc: Use image node_id 2 for calling the ConvLSTM2DTest obj's underlying member method code with example usage: obj.test_correctness() without return types